Methods and framework for constraint-based activity mining (CMAP)
First Claim
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1. A computer-based method of mining data to discover activity patterns within the data, said method comprising:
- receiving data to be mined at a computer framework from at least one data source communicatively coupled to the computer framework;
determining which of a number of specified constraints are available for the mining task, the constraints including a syntactic filter constraint configured to utilize a sequence of modes to filter patterns and avoid generation of patterns with redundant atoms, a semantic filter constraint having a minimum frequency threshold, a sequence of modes and a Boolean expression on arguments in the modes, and at least one of a generation rule constraint, a maximum length constraint, an extended length constraint, and a complex constraint;
selecting corresponding mining agents that combine search algorithms with propagators from at least one of the specified constraints;
finding any activity patterns, using the computer framework, that meet at least one of the specified constraints, each activity pattern including one or more atoms, each atom defined on a predicate that includes one or more typed arguments; and
analyzing the activity patterns, using the computer framework, found to meet at least one of the specified constraints.
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Abstract
A method of mining data to discover activity patterns within the data is described. The method includes receiving data to be mined from at least one data source, determining which of a number of specified interests and constraints are associated with the mining process, selecting corresponding mining agents that combine search algorithms with propagators from the specified constraints, and finding any activity patterns that meet the specified interests and constraints.
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Citations
18 Claims
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1. A computer-based method of mining data to discover activity patterns within the data, said method comprising:
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receiving data to be mined at a computer framework from at least one data source communicatively coupled to the computer framework; determining which of a number of specified constraints are available for the mining task, the constraints including a syntactic filter constraint configured to utilize a sequence of modes to filter patterns and avoid generation of patterns with redundant atoms, a semantic filter constraint having a minimum frequency threshold, a sequence of modes and a Boolean expression on arguments in the modes, and at least one of a generation rule constraint, a maximum length constraint, an extended length constraint, and a complex constraint; selecting corresponding mining agents that combine search algorithms with propagators from at least one of the specified constraints; finding any activity patterns, using the computer framework, that meet at least one of the specified constraints, each activity pattern including one or more atoms, each atom defined on a predicate that includes one or more typed arguments; and analyzing the activity patterns, using the computer framework, found to meet at least one of the specified constraints. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-based system for constraint-based mining of activity patterns within a framework, said system comprising:
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a data input; a plurality of data mining tools within the framework and operable to run on said system, said data mining tools configured to search data received at said data input for one or both of temporal and spatial patterns for activities of interest within one or more scenarios, each pattern including one or more atoms, each atom defined on a predicate that includes one or more typed arguments; a plurality of constraints, said constraints based on knowledge and experiences, and operable to cause said system to determine whether one or more patterns satisfies the said constraints, said constraints organized based on a subsumption relationship among the constraints and including a syntactic filter constraint configured to utilize a sequence of modes to filter patterns and avoid generation of patterns with redundant atoms, a semantic filter constraint having a minimum frequency threshold, a sequence of modes and a Boolean expression on arguments in the modes, and at least one of a generation rule constraint, a maximum length constraint, an extended length constraint, and a complex constraint; and at least one database configured for operation as a pattern repository. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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Specification